1
，我有以下熔化的數據：選擇頂行按值排序後融化的數據
dat.melt <- structure(list(CellTypes = structure(c(62L, 35L, 73L, 45L, 14L,
22L, 46L, 13L, 68L, 21L, 1L, 10L, 64L, 24L, 72L, 58L, 51L, 9L,
60L, 37L, 34L, 49L, 33L, 2L, 50L, 32L, 11L, 52L, 44L, 66L, 8L,
5L, 47L, 59L, 53L, 7L, 6L, 77L, 75L, 17L, 27L, 61L, 20L, 18L,
19L, 16L, 54L, 15L, 41L, 3L, 63L, 48L, 57L, 43L, 70L, 40L, 12L,
76L, 74L, 29L, 28L, 25L, 30L, 42L, 39L, 56L, 4L, 67L, 71L, 31L,
36L, 23L, 38L, 69L, 55L, 26L, 65L, 62L, 35L, 73L, 45L, 14L, 22L,
46L, 13L, 68L, 21L, 1L, 10L, 64L, 24L, 72L, 58L, 51L, 9L, 60L,
37L, 34L, 49L, 33L, 2L, 50L, 32L, 11L, 52L, 44L, 66L, 8L, 5L,
47L, 59L, 53L, 7L, 6L, 77L, 75L, 17L, 27L, 61L, 20L, 18L, 19L,
16L, 54L, 15L, 41L, 3L, 63L, 48L, 57L, 43L, 70L, 40L, 12L, 76L,
74L, 29L, 28L, 25L, 30L, 42L, 39L, 56L, 4L, 67L, 71L, 31L, 36L,
23L, 38L, 69L, 55L, 26L, 65L), .Label = c("3T3-L1", "Adipose Brown",
"Adipose White", "Adrenal Gland", "B Cells (GL7 neg; Alum)",
"B Cells (GL7 neg; KLH)", "B Cells (GL7 pos; Alum)", "B Cells (GL7 pos; KLH)",
"B Cells Marginal Zone", "B220+ Dend. Cells", "BA/F3", "Bladder",
"Bone", "Bone Marrow", "C2C12", "CD4+ SP Thymoctyes", "CD4+ T cells",
"CD4+/CD8+ DP Thymocytes", "CD8+ SP Thymocytes", "CD8+ T cells",
"CD8a+ Dend. Cells Lymphoid", "CD8a+ Dend. Cells Myeloid", "Ciliary Bodies",
"Common Myeloid Progenitor", "Cornea", "Dorsal Root Ganglia",
"Embryonic Fibroblasts", "Embryonic Stem Line Bruce4 P13", "Embryonic Stem Line V26 2 P16",
"Epidermis", "Eyecup", "Follicular B Cells", "Foxp3+ Tcells",
"Granulo Monoprogenitor", "Granulocytes", "Heart", "Hematopoietic Stem Cells",
"Iris", "Kidney", "Lacrimal Gland", "Large Intestine", "Lens",
"Liver", "Lung", "Lymph Nodes", "Macrophage Peri ", "Mammary Gland",
"Mammary Gland Non-Lactating", "Mast Cells", "Mast Cells IgE",
"Mast Cells IgE 1hr", "Mast Cells IgE 6hr", "Megaerythrocyte Progenitor",
"mIMCD-3 Cells", "MIN6 cells", "Neuro2a Neuroblastoma Cells",
"NIH 3T3", "NK Cells", "Osteoblast Day14", "Osteoblast Day21",
"Osteoblast Day5", "Osteoclasts", "Ovary", "Pancreas", "Pituitary",
"Placenta", "Prostate", "RAW 264.7 Cells", "Retinal Pigment Epithelium",
"Salivary Gland", "Skeletal Muscle", "Small Intestine", "Spleen",
"Stem Cells C3H/10T1/2", "Stomach", "Umbilical Cord", "Uterus"
), class = "factor"), variable = structure(c(1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L), .Label = c("LPS_IV_SP", "MPL_IV_SP"), class = "factor"),
value = c(3.647, 33.629, 17.838, 33.917, 29.66, 31.694, 32.603,
24.152, 19.969, 24.012, 40.101, 12.682, 0.323, 12.846, 5.087,
11.707, 16.682, 7.71, 22.472, 10.21, 10.109, 12.643, 12.623,
1.48, 13.075, 5.042, 12.19, 11.691, 15.24, 17.073, 5.854,
5.188, 11.983, 18.679, 6.406, 4.474, 5.445, 8.144, 0.739,
3.652, 14.232, 17.1, 2.603, 1.762, 1.993, 3.475, 10.305,
7.457, 1.189, 2.895, 4.181, 3.06, 5.885, 3.063, 2.532, 1.662,
3.86, 5.094, 5.916, 4.553, 3.703, 2.546, 0.764, 0.597, 1.39,
2.933, 0.665, 0.121, 0.257, 0.764, 0.196, 0.208, 0.232, 0.001,
0.004, 0.035, 0.036, 56.156, 53.485, 48.206, 45.975, 41.067,
40.581, 38.155, 33.009, 29.468, 29.219, 27.945, 19.165, 15.985,
15.682, 15.077, 14.72, 13.856, 13.576, 12.914, 12.77, 12.577,
12.526, 11.05, 10.532, 10.008, 9.942, 9.238, 8.67, 8.237,
7.938, 7.819, 7.55, 7.349, 7.217, 7.146, 6.158, 5.852, 5.368,
5.328, 5.126, 4.887, 4.767, 4.24, 3.858, 3.816, 3.676, 3.318,
3.118, 2.459, 2.269, 2.266, 2.201, 1.467, 1.418, 1.368, 1.267,
1.077, 1.022, 0.835, 0.667, 0.655, 0.609, 0.53, 0.452, 0.24,
0.239, 0.211, 0.124, 0.084, 0.05, 0.028, 0.024, 0.016, 0.007,
0.006, 0.003, 0.002)), row.names = c(NA, -154L), .Names = c("CellTypes",
"variable", "value"), class = "data.frame")
它看起來像這樣：
> tail(dat.melt,n=5L)
CellTypes variable value
150 Iris MPL_IV_SP 0.016
151 Retinal Pigment Epithelium MPL_IV_SP 0.007
152 MIN6 cells MPL_IV_SP 0.006
153 Dorsal Root Ganglia MPL_IV_SP 0.003
154 Pituitary MPL_IV_SP 0.002
> head(dat.melt,n=5L)
CellTypes variable value
1 Osteoclasts LPS_IV_SP 3.647
2 Granulocytes LPS_IV_SP 33.629
3 Spleen LPS_IV_SP 17.838
4 Lymph Nodes LPS_IV_SP 33.917
5 Bone Marrow LPS_IV_SP 29.660
>
對於每個變量MPL_IV_SP和LPS_IV_SP我想選擇最前-5行（'單元格類型'）按值降序排列。我怎樣才能做到這一點？